Discrete choice and microsimulation methods for agent-based land use modeling

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The optimal pricing of goods, especially when they are new and the innovating firm is a monopolist, must proceed without precise knowledge of the demand curve. This paper provides a pricing method with a relative robustness guarantee by maximizing a perfor ...

Zoning reform is a crucial tool for cities to adapt to contemporary challenges. However, its implementation remains challenging. Property owners, with a vested interest in the value of their neighborhoods, are sensitive to local developments and the potent ...

Beliefs inform the behaviour of forward-thinking agents in complex environments. Recently, sequential Bayesian inference has emerged as a mechanism to study belief formation among agents adapting to dynamical conditions. However, we lack critical theory to ...

This repository contains microphysics routines, scripts, and processed data from the Weather Research and Forecasting (WRF) model simulations presented in the paper "RaFSIP: Parameterizing ice multiplication in models using a machine learning approach", by ...

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

We introduce a new measure of the price charged by ﬁnancial intermediaries for con-necting mortgage borrowers with capital market investors. Based on administrativelender pricing data, we document that the price of intermediation reacts stronglyto variatio ...

Anthropogenic modification of natural landscapes to urban environments impacts land-atmosphere interactions in the boundary layer. Ample research has demonstrated the effect of such landscape transitions on development of the urban heat island (UHI), but c ...

This repository contains field observations and processed data from the Weather Research and Forecasting (WRF) model simulations and the Cloud Resolving Model Radar Simulator (CR-SIM), alongside scripts designed to reproduce the figures presented in the pa ...

Cortical dynamics underlie many cognitive processes and emerge from complex multi-scale interactions, which are challenging to study in vivo. Large-scale, biophysically detailed models offer a tool which can complement laboratory approaches. We present a m ...

Reinforcement learning (RL) has shown promising results for real-time control systems, including the domain of plasma magnetic control. However, there are still significant drawbacks compared to traditional feedback control approaches for magnetic confinem ...

Why have countries formerly leading public policies of housing – Norway, the U.K., France, etc. – shifted towards privatizing accommodation from the late 1970s? Have these States merely let go of housing and handed it over to private interests in the name ...

Macroscopic fundamental diagrams (MFDs) have been widely adopted to model the traffic flow of large-scale urban networks. Coupling perimeter control and regional route guidance (PCRG) is a promising strategy to decrease congestion heterogeneity and reduce ...

Uncertainty of spillover effects – including property devaluation - from proposed land-use change elicits opposition to local development. This hinders cities’ ability to implement land-use policy aimed at housing affordability and environmental sustainabi ...

In this paper, we propose an analytical stochastic dynamic programming (SDP) algorithm to address the optimal management problem of price-maker community energy storage. As a price-maker, energy storage smooths price differences, thus decreasing energy arb ...

The CA1 region of the hippocampus is one of the most studied regions of the rodent brain, thought to play an important role in cognitive functions such as memory and spatial navigation. Despite a wealth of experimental data on its structure and function, i ...

Wearable and implantable medical devices are of great importance in diagnosis and treatment as they provide continuous monitoring and data collection. Considering the comfort of the patient and ease-of-operation, these devices require wireless data transmi ...

As large, data-driven artificial intelligence models become ubiquitous, guaranteeing high data quality is imperative for constructing models. Crowdsourcing, community sensing, and data filtering have long been the standard approaches to guaranteeing or imp ...

Modern neuroscience research is generating increasingly large datasets, from recording thousands of neurons over long timescales to behavioral recordings of animals spanning weeks, months, or even years. Despite a great variety in recording setups and expe ...

Image information about the state of a building after an earthquake, which can be collected without endangering the post-earthquake reconnaissance activities, can be used to reduce uncertainties in response predictions for future seismic events. This paper ...

Dataset corresponding to the following manuscript: Slagter, A., Setyadji, J.A., Vogt, E.L. et al. Nanoindentation Hardness and Modulus of Al2O3–SiO2–CaO and MnO–SiO2–FeO Inclusions in Iron. Metall Mater Trans A (2024). https://doi.org/10.1007/s11661-024-0 ...

Discrete choice and microsimulation methods for agent-based land use modeling

Chattez avec Graph Search

Monopoly Pricing with Unknown Demand

Spatial Modeling for Building Design Evaluation: from Visual Landscape Quality Assessment to Devaluation Risk Estimation

Stochastic pairwise preference convergence in Bayesian agents

Data and scripts for the RaFSIP scheme

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

The Time‐Varying Price of Financial Intermediation in the Mortgage Market

Urban boundary-layer flows in complex terrain: Dynamic interactions during a hot and dry summer season in Phoenix, Arizona

Data and scripts for "Unraveling secondary ice production in winter orographic clouds through a synergy of in-situ observations, remote sensing and modeling"

Modeling and simulation of neocortical micro- and mesocircuitry. Part II: Physiology and experimentation

Towards practical reinforcement learning for tokamak magnetic control

Frihet, sikkerhet, forstaden: Brev fra Amerika

An Iterative Adaptive Dynamic Programming Approach for Macroscopic Fundamental Diagram-Based Perimeter Control and Route Guidance

Using automated design appraisal to model building-specific devaluation risk due to land-use change

Energy Management of Price-Maker Community Energy Storage by Stochastic Dynamic Programming

Community-based reconstruction and simulation of a full-scale model of region CA1 of rat hippocampus

An area efficient inductorless super-regenerative receiver front-end for biomedical implant devices

Extensions of Peer Prediction Incentive Mechanisms

Robust machine learning for neuroscientific inference

Reducing uncertainties in response predictions of earthquake-damaged masonry buildings using data from image-based inspection

Nanoindentation hardness and modulus of Al2O3-SiO2-CaO and MnO-SiO2-FeO inclusions in iron